An automated character recognition system, such as an optical character recognition (OCR) system, may be presented with characters in different fonts or handwriting, of poor print quality, and at a slant relative to the image axis. These inconsistencies introduce uncertainty in the character assignments made by the automated character recognition system. In some instances the system may not be able to positively distinguish between a particular character and a different character whose geometry is different but that is roughly similar. As a result, the automated character recognition system may incorrectly identify a character (i.e. make an error in selecting the correct character assignment) or may require the character assignment be made by human intervention. To improve the efficiency of automated character recognition, it is desirable to improve the ability of the automated character recognition system to distinguish characters having similar geometry.